Enterprise software systems receive, generate, and store analytical data related to enterprise transactions. Some of this analytical data may include data generated by sensors in response to activities occurring within disparate physical spaces. The volume of this “spatial” data is increasing rapidly as the Internet-of-Things becomes more prevalent.
Users operate software tools to access analytical data and display the data in useful formats, such as in graphic visualizations. Visualizations may facilitate the detection of patterns within the data and the determination of insights from the data. However, it is difficult to analyze spatial data without relating the corresponding analytical spaces to particular enterprise entities or activities.
Conventional attempts to address the foregoing include complex functional programming and materialization of the results. What is needed is a system to dynamically view analytical data from a perspective different from those provided by the data model of the analytical data.